[id=YS]As part of the Instance Space Analysis, we build algorithm selection models using machine learning [1]}, [2]}, [3]}, to identify which algorithm is most effective in a particular region of the instance space. We select three state-of-the-art algorithms from the literature as our candidates: the Lagrangian relaxation and ACO hybrid [4]} and two LNS algorithms proposed by [5]}. Additionally, given the vast improvement in commercial solvers, we investigate three algorithms not previously successful or attempted in the literature. These are MIP, MIP based on lazy constraints, and an improved LNS (an extension of the algorithms studied in [5]}).
